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提交 3126f874 authored 作者: dumitru@deepnets.mtv.corp.google.com's avatar dumitru@deepnets.mtv.corp.google.com
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Backporting code to work with Python 2.4

Summary of changes: - Added implementations of functools.partial, defaultdict, any, all - Re-wrote relative imports to be absolute imports - Re-wrote conditional expressions to normal if/else expressions
上级 fc3d3432
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正在显示 包含 525 行增加 和 136 行删除
theano/__init__.py
浏览文件 @ 3126f874
......@@ -24,6 +24,7 @@ To learn more, check out:
"""
__docformat__ = "restructuredtext en"
import gof
from gof import \
CLinker, OpWiseCLinker, DualLinker, Linker, LocalLinker, PerformLinker, \
......
theano/compile/builders.py
浏览文件 @ 3126f874
from .. import gof
from .. import gradient as G
from theano import gof
from theano import gradient as G
from function_module import function
......
theano/compile/debugmode.py
浏览文件 @ 3126f874
......@@ -6,19 +6,19 @@ from StringIO import StringIO
import numpy
from .. import gof
from ..gof import Env, graph, utils, link
from ..gof.link import WrapLinkerMany, raise_with_op
from ..gof.cutils import run_cthunk
from ..gof.cc import OpWiseCLinker, CLinker
from ..compile.function_module import (FunctionMaker,
from theano import gof
from theano.gof import Env, graph, utils, link
from theano.gof.link import WrapLinkerMany, raise_with_op
#from theano.gof.cutils import run_cthunk
from theano.gof.cc import OpWiseCLinker, CLinker
from theano.compile.function_module import (FunctionMaker,
Function,
infer_reuse_pattern,
SymbolicInput,
SymbolicInputKit,
SymbolicOutput,
Supervisor)
from ..compile.mode import Mode, register_mode
from theano.compile.mode import Mode, register_mode
########################
......@@ -221,7 +221,10 @@ def _debugprint(r, prefix='', depth=-1, done=None, file=sys.stdout):
"""
if depth==0:
return
done = set() if done is None else done
#backport
if done is None:
done = set()
#done = set() if done is None else done
if hasattr(r.owner, 'op'):
# this variable is the output of computation,
# so just print out the apply
......@@ -509,9 +512,15 @@ def _find_bad_optimizations2(order, reasons, r_vals):
checked_variables.add(r)
# (recursively) first check all the variables that could make r look bad:
list_of_vars = [old_r for (reason, old_r, olds, news) in reasons[r]]
if (None is not r.owner):
list_of_vars += r.owner.inputs
for var_that_could_make_r_look_bad in \
[old_r for (reason, old_r, olds, news) in reasons[r]] \
+ ([] if (None is r.owner) else r.owner.inputs):
list_of_vars:
#backport
#[old_r for (reason, old_r, olds, news) in reasons[r]] \
#+ ([] if (None is r.owner) else r.owner.inputs):
check_variable(var_that_could_make_r_look_bad)
check_variable_norec(r)
......@@ -559,11 +568,18 @@ class _EnvEvent(object):
def __str__(self):
if self.kind == 'change':
if (self.op != 'output'):
msg = str(len(self.node.inputs))
else:
msg = ''
return ' '.join(['change',
self.reason,
str(self.op),
str(self.idx),
str(len(self.node.inputs)) if (self.op != 'output') else ''])
msg])
#backport
#str(len(self.node.inputs)) if (self.op != 'output') else ''])
else:
return str(self.__dict__)
......@@ -1015,7 +1031,7 @@ class _Maker(FunctionMaker): #inheritance buys a few helper functions
# WARNING: this is a global mechanism... so it will screw up if we are trying to use
# multiple modes at once.
from ..tensor import TensorType #to set filter_check_isfinite
from theano.tensor import TensorType #to set filter_check_isfinite
TensorType.filter_checks_isfinite = mode.check_isfinite
# Handle the case where inputs and/or outputs is a single Variable (not in a list)
......@@ -1053,8 +1069,19 @@ class _Maker(FunctionMaker): #inheritance buys a few helper functions
for j in xrange(max(len(li), len(l0))):
if j >= len(li) or j >= len(l0) or li[j] != l0[j]:
print >> infolog, "* ", j,
print >> infolog, " ", str(li[j]) if j < len(li) else '-',
print >> infolog, " ", str(l0[j]) if j < len(l0) else '-'
if j < len(li):
msg = str(li[j])
else:
msg = '-'
print >> infolog, " ", msg
if j < len(l0):
msg = str(l0[j])
else:
msg = '-'
print >> infolog, " ", msg
#backport
#print >> infolog, " ", str(li[j]) if j < len(li) else '-',
#print >> infolog, " ", str(l0[j]) if j < len(l0) else '-'
else:
pass
raise StochasticOrder(infolog.getvalue())
......
theano/compile/function_module.py
浏览文件 @ 3126f874
......@@ -6,11 +6,14 @@ __docformat__ = "restructuredtext en"
import copy_reg
import cPickle
from functools import partial
import sys
if sys.version_info[:2] >= (2,5):
from functools import partial
import numpy
from .. import gof
import sys
import theano.gof
#from theano import gof
import copy
import mode as mode_module
......@@ -33,8 +36,18 @@ def infer_reuse_pattern(env, outputs_to_disown):
do_not_reuse.append(r)
node = r.owner
op = node.op
dmap = op.destroy_map if hasattr(op, 'destroy_map') else {}
vmap = op.view_map if hasattr(op, 'view_map') else {}
if hasattr(op, 'destroy_map'):
dmap = op.destroy_map
else:
dmap = {}
if hasattr(op, 'view_map'):
vmap = op.view_map
else:
vmap = {}
#backport
#dmap = op.destroy_map if hasattr(op, 'destroy_map') else {}
#vmap = op.view_map if hasattr(op, 'view_map') else {}
for l in dmap.values() + vmap.values():
for i in l:
walk(node.inputs[i])
......@@ -252,7 +265,12 @@ class Function(object):
c.provided = 0 # this is a count of how many times the input has been provided (reinitialized to 0 on __call__)
finder[i] = c
finder[input.variable] = c
finder[input.name] = c if input.name not in finder else DUPLICATE
if input.name not in finder:
finder[input.name] = c
else:
finder[input.name] = DUPLICATE
#backport
#finder[input.name] = c if input.name not in finder else DUPLICATE
# inv_finder maps the container to the input (useful for one error message)
inv_finder[c] = input
#setters.append(partial(assign, c))
......@@ -271,7 +289,12 @@ class Function(object):
# can reinitialize all the containers
finder[i] = f
finder[input] = f
finder[input.name] = f if input.name not in finder else DUPLICATE
if input.name not in finder:
finder[input.name] = f
else:
finder[input.name] = DUPLICATE
#backport
#finder[input.name] = f if input.name not in finder else DUPLICATE
#setters.append(f)
# For each input in the kit and its corresponding container, we put an entry in finder.
# This allows the user to micro-manage elements of the kit if need be.
......@@ -279,7 +302,12 @@ class Function(object):
for c, sin in zip(cs, sinputs):
finder[sin.variable] = c
finder[sin.name] = c
finder[sin.name] = c if sin.name not in finder else DUPLICATE
if sin.name not in finder:
finder[sin.name] = c
else:
finder[sin.name] = DUPLICATE
#backport
#finder[sin.name] = c if sin.name not in finder else DUPLICATE
inv_finder[c] = input
c.required = required
c.provided = 0
......@@ -507,9 +535,15 @@ class SanityCheckFunction(Function):
if not input.mutable:
if not self.check_equal(c1.value, c2.value):
name = c2.name
if name:
the_name = name
else:
the_name = ""
raise ValueError("Input #%i%s using %s and %s differs."
% (i,
" (%s)" % name if name else "",
#backport
#" (%s)" % name if name else "",
" (%s)" % the_name,
self.maker.mode,
fn.maker.mode),
c1.value, c2.value)
......@@ -520,9 +554,15 @@ class SanityCheckFunction(Function):
r2 = c2.value
if not self.check_equal(r1, r2):
name = c2.name
if name:
the_name = name
else:
the_name = ""
raise ValueError("Variable #%i%s using %s and %s differs."
% (i,
" (%s)" % name if name else "",
#backport
#" (%s)" % name if name else "",
" (%s)" % the_name,
self.maker.mode,
fn.maker.mode),
r1, r2)
......@@ -598,7 +638,10 @@ class FunctionMaker(object):
in the graph from the inputs to the outputs
"""
mode = mode if mode is not None else mode_module.default_mode
if mode is None:
mode = mode_module.default_mode
#backport
#mode = mode if mode is not None else mode_module.default_mode
# Handle the case where inputs and/or outputs is a single Variable (not in a list)
unpack_single = False
......@@ -703,7 +746,16 @@ class FunctionMaker(object):
def _pickle_FunctionMaker(fm):
outputs = None if fm.return_none else (fm.outputs[0] if fm.unpack_single else fm.outputs)
if fm.return_none:
outputs = None
else:
if fm.unpack_single:
outputs = fm.outputs[0]
else:
outputs = fm.outputs
#backport
#outputs = None if fm.return_none else (fm.outputs[0] if fm.unpack_single else fm.outputs)
rval = (_constructor_FunctionMaker, (fm.inputs, outputs, fm.mode, fm.accept_inplace))
return rval
......@@ -788,12 +840,19 @@ def function(inputs, outputs, mode=None, accept_inplace = False):
f[<kitname>] = seed #re-seed the elements of a RandomKit
"""
mode = mode if mode is not None else mode_module.default_mode
if mode is None:
mode = mode_module.default_mode
#backport
#mode = mode if mode is not None else mode_module.default_mode
inputs = map(convert_function_input, inputs)
if outputs is not None:
outputs = map(FunctionMaker.wrap_out, outputs) if isinstance(outputs, (list, tuple)) else FunctionMaker.wrap_out(outputs)
if isinstance(outputs, (list, tuple)):
outputs = map(FunctionMaker.wrap_out, outputs)
else:
outputs = FunctionMaker.wrap_out(outputs)
#backport
#outputs = map(FunctionMaker.wrap_out, outputs) if isinstance(outputs, (list, tuple)) else FunctionMaker.wrap_out(outputs)
defaults = [getattr(input, 'value', None) for input in inputs]
......@@ -807,9 +866,17 @@ def function(inputs, outputs, mode=None, accept_inplace = False):
#return a different kind of function
def dup_defaults():
# TODO This may need to be changed to use containers as defaults.
return [copy.copy(default.value) if isinstance(default, gof.Container) else
copy.copy(default)
for default in defaults]
retval = []
for default in defaults:
if isinstance(default, gof.Container):
retval +=[copy.copy(default.value)]
else:
retval +=[copy.copy(default)]
return retval
#backport
#return [copy.copy(default.value) if isinstance(default, gof.Container) else
# copy.copy(default)
# for default in defaults]
makers = [FunctionMaker(inputs, outputs, m, accept_inplace = accept_inplace) for m in mode[1:]]
fns = [maker.create(dup_defaults(), trustme = True) for maker in makers]
builder = partial(SanityCheckFunction, fns, check_equal)
......
theano/compile/io.py
浏览文件 @ 3126f874
......@@ -39,11 +39,23 @@ class SymbolicInput(object):
implicit=False):
assert implicit is not None # Safety check.
self.variable = variable
self.name = variable.name if (autoname and name is None) else name
if (autoname and name is None):
self.name = variable.name
else:
self.name = name
#backport
#self.name = variable.name if (autoname and name is None) else name
if self.name is not None and not isinstance(self.name, str):
raise TypeError("name must be a string! (got: %s)" % self.name)
self.update = update
self.mutable = mutable if (mutable is not None) else (update is not None)
if (mutable is not None):
self.mutable = mutable
else:
self.mutable = (update is not None)
#backport
#self.mutable = mutable if (mutable is not None) else (update is not None)
self.strict = strict
self.implicit = implicit
......
theano/compile/module.py
浏览文件 @ 3126f874
......@@ -8,10 +8,14 @@ __docformat__ = "restructuredtext en"
from theano import gof
from theano.printing import pprint
from collections import defaultdict
from itertools import chain
from functools import partial
import io, sys
if sys.version_info[:2] >= (2,5):
from collections import defaultdict
from itertools import chain
if sys.version_info[:2] >= (2,5):
from functools import partial
import function_module as F
import mode as get_mode
......@@ -418,8 +422,26 @@ class Method(Component):
outputs = self.outputs
_inputs = [x.variable for x in inputs]
# Grab the variables that are not accessible from either the inputs or the updates.
outputs_list = [] if outputs is None else (list(outputs) if isinstance(outputs, (list, tuple)) else [outputs])
outputs_variable_list = [o.variable if isinstance(o, io.Out) else o for o in outputs_list]
if outputs is None:
outputs_list = []
else:
if isinstance(outputs, (list, tuple)):
outputs_list = list(outputs)
else:
outputs_list = [outputs]
#backport
#outputs_list = [] if outputs is None else (list(outputs) if isinstance(outputs, (list, tuple)) else [outputs])
outputs_variable_list = []
for o in outputs_list:
if isinstance(o, io.Out):
outputs_variable_list += [o.variable]
else:
outputs_variable_list += [o]
#backport
#outputs_variable_list = [o.variable if isinstance(o, io.Out) else o for o in outputs_list]
for input in gof.graph.inputs(outputs_variable_list
+ [x.update for x in inputs if getattr(x, 'update', False)],
blockers = _inputs):
......@@ -448,7 +470,13 @@ class Method(Component):
assert type(storage) is io.In
inputs.append(storage)
effective_mode = mode if self.mode is None else self.mode
if self.mode is None:
effective_mode = mode
else:
effective_mode = self.mode
#backport
#effective_mode = mode if self.mode is None else self.mode
rval = F.function(inputs, outputs, effective_mode)
memo[self] = rval
return rval
......@@ -459,7 +487,13 @@ class Method(Component):
rval = 'inputs: %s\n' % ", ".join(map(str, self.inputs))
else:
rval = ''
inputs, outputs, updates = self.inputs, self.outputs if isinstance(self.outputs, (list, tuple)) else [self.outputs], self.updates
if isinstance(self.outputs, (list, tuple)):
inputs, outputs, updates = self.inputs, self.outputs
else:
inputs, outputs, updates = [self.outputs], self.updates
#backport
#inputs, outputs, updates = self.inputs, self.outputs if isinstance(self.outputs, (list, tuple)) else [self.outputs], self.updates
# If mode is in kwargs, prints the optimized version of the method
mode = kwargs.pop('mode', None)
......@@ -472,10 +506,16 @@ class Method(Component):
return rval
def __str__(self):
if self.updates:
sep = "; "
else:
sep = ""
return "Method(%s -> %s%s%s)" % \
(self.inputs,
self.outputs,
"; " if self.updates else "",
sep,
#backport
#"; " if self.updates else "",
", ".join("%s <= %s" % (old, new) for old, new in self.updates.iteritems()))
def __call__(self, *args, **kwargs):
......@@ -603,7 +643,16 @@ class Composite(Component):
self.set(item, value)
def __iter__(self):
return (c.r if isinstance(c, (External, Member)) else c for c in self.components())
retval = []
for c in self.components():
if isinstance(c, (External, Member)):
retval += [c.r]
else:
retval += [c]
return retval
#backport
#return (c.r if isinstance(c, (External, Member)) else c for c in self.components())
......@@ -1047,7 +1096,12 @@ class Module(ComponentDict):
# Function to go through member lists and dictionaries recursively,
# to look for submodules on which make_module_instance needs to be called
def recurse(v):
iter = enumerate(v) if isinstance(v,list) else v.iteritems()
if isinstance(v,list):
iter = enumerate(v)
else:
iter = v.iteritems()
#backport
#iter = enumerate(v) if isinstance(v,list) else v.iteritems()
for sk,sv in iter:
if isinstance(sv,(list,dict)):
sv = recurse(sv)
......
theano/compile/profilemode.py
浏览文件 @ 3126f874
import time, atexit
from ..gof.link import WrapLinkerMany
from ..gof.cutils import run_cthunk
from ..compile.mode import Mode, predefined_linkers, register_mode, predefined_modes
from ..gof.cc import OpWiseCLinker
from theano.gof.link import WrapLinkerMany
from theano.gof.cutils import run_cthunk
from theano.compile.mode import Mode, predefined_linkers, register_mode, predefined_modes
from theano.gof.cc import OpWiseCLinker
class ProfileMode(Mode):
def __init__(self, linker=OpWiseCLinker(), optimizer=None):
......@@ -82,7 +82,13 @@ class ProfileMode(Mode):
tot=0
for f,t,a,ci in otimes[:n_ops_to_print]:
tot+=t
print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, '*' if ci else ' ', a)
if ci:
msg = '*'
else:
msg = ' '
print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, msg, a)
#backport
#print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, '*' if ci else ' ', a)
print ' ... (remaining %i Ops account for %.2f%%(%.2fs) of the runtime)'\
%(max(0, len(otimes)-n_ops_to_print),
sum(f for f, t, a, ci in otimes[n_ops_to_print:])*100,
......@@ -104,7 +110,13 @@ class ProfileMode(Mode):
tot=0
for f,t,a,ci in sotimes[:n_ops_to_print]:
tot+=t
print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, '*' if ci else ' ', a)
if ci:
msg = '*'
else:
msg = ' '
print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, msg, a)
#backport
#print ' %.2f%% %.3fs %.3fs %s %s' % (f*100, tot, t, '*' if ci else ' ', a)
print ' ... (remaining %i Ops account for %.2f%%(%.2fs) of the runtime)'\
%(max(0, len(sotimes)-n_ops_to_print),
sum(f for f, t, a in sotimes[n_ops_to_print:])*100,
......
theano/gof/callcache.py
浏览文件 @ 3126f874
......@@ -29,13 +29,21 @@ class CallCache(object):
self.cache = {}
def persist(self, filename=None):
filename = self.filename if filename is None else filename
if filename is None:
filename = self.filename
#backport
#filename = self.filename if filename is None else filename
f = file(filename, 'w')
cPickle.dump(self.cache, f)
f.close()
def call(self, fn, args=(), key=None):
key = (fn, tuple(args)) if key is None else key
if key is None:
key = (fn, tuple(args))
#backport
#key = (fn, tuple(args)) if key is None else key
if key not in self.cache:
debug('cache miss', len(self.cache))
self.cache[key] = fn(*args)
......
theano/gof/cc.py
浏览文件 @ 3126f874
......@@ -5,7 +5,10 @@ Defines Linkers that deal with C implementations.
# Python imports
from copy import copy
import re #for set_compiledir
import os, sys, platform, StringIO, time, hashlib
import os, sys, platform, StringIO, time
import md5
if sys.version_info[:2] >= (2,5):
import hashlib
# weave import
from scipy import weave
......@@ -37,7 +40,7 @@ def error(*args):
sys.stderr.write('ERROR:'+ ' '.join(str(a) for a in args)+'\n')
_logger.error(' '.join(str(a) for a in args))
from .callcache import CallCache
from theano.gof.callcache import CallCache
def get_module_cache():
return cmodule.get_module_cache(get_compiledir())
......@@ -514,7 +517,12 @@ class CLinker(link.Linker):
# The hash calculated on the code identifies it so weave can cache properly.
# (the hash has to be used outside of the support code because weave does not consider changes in the support code)
hash = hashlib.md5(struct_code).hexdigest()
# hashlib is new to 2.5
if sys.version_info[:2] < (2,5):
hash = md5.new(struct_code).hexdigest()
else:
hash = hashlib.md5(struct_code).hexdigest()
struct_name = '__struct_compiled_op_%s' % hash
#struct_code %= dict(name = struct_name)
struct_code = re.sub("<<<<NAME>>>>", struct_name, struct_code)
......@@ -769,7 +777,10 @@ class CLinker(link.Linker):
"""
This method is a callback for `ModuleCache.module_from_key`
"""
location = get_compiledir() if location is None else location
if location is None:
location = get_compiledir()
#backport
#location = get_compiledir() if location is None else location
mod = self.build_dynamic_module()
get_lock()
try:
......
theano/gof/cmodule.py
浏览文件 @ 3126f874
......@@ -237,7 +237,12 @@ class ModuleCache(object):
self.module_from_name = dict(self.module_from_name)
self.entry_from_key = dict(self.entry_from_key)
self.stats = [0, 0, 0]
self.force_fresh = self.force_fresh if force_fresh is None else force_fresh
if force_fresh is None:
self.force_fresh = self.force_fresh
else:
self.force_fresh = force_fresh
#backport
#self.force_fresh = self.force_fresh if force_fresh is None else force_fresh
self.loaded_key_pkl = set()
self.refresh()
......@@ -393,7 +398,11 @@ class ModuleCache(object):
:param age_thresh: dynamic modules whose last access time is more than ``age_thresh``
seconds ago will be erased.
"""
age_thresh = self.age_thresh if age_thresh is None else age_thresh
if age_thresh is None:
age_thresh = self.age_thresh
#backport
#age_thresh = self.age_thresh if age_thresh is None else age_thresh
compilelock.get_lock()
try:
# update the age of modules that have been accessed by other processes
......@@ -474,7 +483,14 @@ def get_gcc_shared_library_arg():
def gcc_module_compile_str(module_name, src_code, location=None, include_dirs=[], lib_dirs=[], libs=[],
preargs=[], tmpdir=None):
#TODO: don't to the dlimport in this function
preargs= [] if preargs is None else list(preargs)
if preargs is None:
preargs = []
else:
preargs = list(preargs)
#backport
#preargs= [] if preargs is None else list(preargs)
preargs.append('-fPIC')
no_opt = False
......@@ -537,7 +553,13 @@ def gcc_module_compile_str(module_name, src_code, location=None, include_dirs=[]
def nvcc_module_compile_str(module_name, src_code, location=None, include_dirs=[], lib_dirs=[], libs=[],
preargs=[], tmpdir=None):
preargs= [] if preargs is None else list(preargs)
if preargs is None:
preargs = []
else:
preargs = list(preargs)
#backport
#preargs= [] if preargs is None else list(preargs)
preargs.append('-fPIC')
no_opt = False
......
theano/gof/destroyhandler.py
浏览文件 @ 3126f874
"""WRITEME"""
from collections import defaultdict
import sys
if sys.version_info[:2] >= (2,5):
from collections import defaultdict
# otherwise it's implemented in python25.py
import toolbox
import graph
......
theano/gof/link.py
浏览文件 @ 3126f874
......@@ -138,7 +138,11 @@ class Container(object):
self.type = r
else:
self.type = r.type
self.name = r.name if name is None else name
if name is None:
self.name = r.name
#backport
#self.name = r.name if name is None else name
self.storage = storage
self.readonly = readonly
self.strict = strict
......
theano/gof/opt.py
浏览文件 @ 3126f874
......@@ -4,6 +4,7 @@ amount of useful generic optimization tools.
"""
import sys
import graph
from env import InconsistencyError
import utils
......@@ -11,9 +12,13 @@ import unify
import toolbox
import op
from copy import copy
from collections import deque, defaultdict
from theano.gof.python25 import any, all
#if sys.version_info[:2] >= (2,5):
# from collections import defaultdict
from collections import deque
import destroyhandler as dh
import sys
import traceback
_optimizer_idx = [0]
......@@ -900,7 +905,12 @@ class EquilibriumOptimizer(NavigatorOptimizer):
max_use_abort = True
else:
lopt_change = self.process_node(env, node, lopt)
process_count[lopt] += 1 if lopt_change else 0
if lopt_change:
process_count[lopt] += 1
else:
process_count[lopt] += 0
#backport
#process_count[lopt] += 1 if lopt_change else 0
changed |= lopt_change
finally:
self.detach_updater(env, u)
......
theano/gof/optdb.py
浏览文件 @ 3126f874
import sys
if sys.version_info[:2] >= (2,5):
from collections import defaultdict
else:
from python25 import defaultdict
from collections import defaultdict
import opt
......
theano/gof/python25.py
浏览文件 @ 3126f874
......@@ -23,6 +23,42 @@ if sys.version_info[:2] < (2,5):
newfunc.args = args
newfunc.keywords = keywords
return newfunc
class defaultdict(dict):
def __init__(self, default_factory=None, *a, **kw):
if (default_factory is not None and
not hasattr(default_factory, '__call__')):
raise TypeError('first argument must be callable')
dict.__init__(self, *a, **kw)
self.default_factory = default_factory
def __getitem__(self, key):
try:
return dict.__getitem__(self, key)
except KeyError:
return self.__missing__(key)
def __missing__(self, key):
if self.default_factory is None:
raise KeyError(key)
self[key] = value = self.default_factory()
return value
def __reduce__(self):
if self.default_factory is None:
args = tuple()
else:
args = self.default_factory,
# consider replacing items() with iteritems()
return type(self), args, None, None, self.items()
def copy(self):
return self.__copy__()
def __copy__(self):
return type(self)(self.default_factory, self)
def __deepcopy__(self, memo):
import copy
return type(self)(self.default_factory,
copy.deepcopy(self.items()))
def __repr__(self):
return 'defaultdict(%s, %s)' % (self.default_factory,
dict.__repr__(self))
else:
# Only bother with this else clause and the __all__ line if you are putting
# this in a separate file.
......
theano/gof/toolbox.py
浏览文件 @ 3126f874
import sys
if sys.version_info[:2] >= (2,5):
from functools import partial
from functools import partial
import graph
import sys
class AlreadyThere(Exception):
......
theano/printing.py
浏览文件 @ 3126f874
......@@ -32,7 +32,13 @@ class Print(Op):
xout[0] = xin
for attr in self.attrs:
temp = getattr(xin, attr)
print self.message, attr,'=', temp() if callable(temp) else temp
if callable(temp):
pmsg = temp()
else:
psmg = temp
print self.message, attr,'=', pmsg
#backport
#print self.message, attr,'=', temp() if callable(temp) else temp
def grad(self,input,output_gradients):
return output_gradients
......@@ -233,7 +239,12 @@ class PPrinter:
strings.append((i + 1000, "%s <- %s" % (name, pprinter.process(output))))
i += 1
if output.name is not None or output in outputs:
name = 'out[%i]' % outputs.index(output) if output.name is None else output.name
if output.name is None:
name = 'out[%i]' % outputs.index(output)
else:
name = output.name
#backport
#name = 'out[%i]' % outputs.index(output) if output.name is None else output.name
current = output
try:
idx = 2000 + outputs.index(output)
......
theano/scalar/basic.py
浏览文件 @ 3126f874
差异被折叠。
theano/sparse/basic.py
浏览文件 @ 3126f874
......@@ -12,10 +12,10 @@ from scipy import sparse
import scipy.sparse
from theano.printing import Print
from .. import gof
from .. import tensor
from .. import compile
from .. import scalar
from theano import gof
from theano import tensor
from theano import compile
from theano import scalar
#TODO: move this decorator to the compile submodule
def register_specialize(lopt, *tags, **kwargs):
......@@ -273,7 +273,12 @@ class CSMProperties(gof.Op):
[data, tensor.ivector(), tensor.ivector(), tensor.ivector()])
def perform(self, node, (csm,), out):
out[0][0] = csm.data if self.kmap is None else csm.data[self.kmap]
if self.kmap is None:
out[0][0] = csm.data
else:
out[0][0] = csm.data[self.kmap]
#backport
#out[0][0] = csm.data if self.kmap is None else csm.data[self.kmap]
out[1][0] = numpy.asarray(csm.indices, dtype='int32')
out[2][0] = numpy.asarray(csm.indptr, dtype='int32')
out[3][0] = numpy.asarray(csm.shape, dtype='int32')
......@@ -1082,8 +1087,19 @@ register_specialize(local_structured_dot)
def structured_dot_grad(sparse_A, dense_B, ga):
if sparse_A.type.format in ('csc','csr'):
sdgcsx = sdg_csc if sparse_A.type.format == 'csc' else sdg_csr
CSx = CSC if sparse_A.type.format == 'csc' else CSR
if sparse_A.type.format == 'csc':
sdgcsx = sdg_csc
else:
sdgcsx = sdg_csr
#backport
#sdgcsx = sdg_csc if sparse_A.type.format == 'csc' else sdg_csr
if sparse_A.type.format == 'csc':
CSx = CSC
else:
CSx = CSR
#backport
#CSx = CSC if sparse_A.type.format == 'csc' else CSR
g_A_data = sdgcsx(csm_indices(sparse_A),\
csm_indptr(sparse_A), dense_B, ga)
......
theano/tensor/basic.py
浏览文件 @ 3126f874
差异被折叠。
theano/tensor/blas.py
浏览文件 @ 3126f874
......@@ -3,19 +3,19 @@
import os, sys, traceback
import numpy
from ..gof import (utils, Op, Apply, view_roots, PatternSub, DestroyHandler,
from theano.gof import (utils, Op, Apply, view_roots, PatternSub, DestroyHandler,
SeqOptimizer, local_optimizer, LocalOptimizer, OpKeyOptimizer,
InconsistencyError)
from ..printing import pprint, FunctionPrinter
from .opt import register_specialize, out2in, insert_inplace_optimizer
from theano.printing import pprint, FunctionPrinter
from theano.tensor.opt import register_specialize, out2in, insert_inplace_optimizer
# opt.py
import basic as T
#NB: this clobbers the builtin 'compile' symbol
from .. import compile #to register the optimizer built by this file
from theano import compile #to register the optimizer built by this file
from .blas_headers import cblas_header_text, blas_header_text
from theano.tensor.blas_headers import cblas_header_text, blas_header_text
@utils.memoize
def ldflags(libs=True, flags=False):
......@@ -365,9 +365,16 @@ gemm = Gemm()
pprint.assign(gemm, FunctionPrinter('gemm'))
def res_is_a(node, op, maxclients=None):
return node.owner \
if maxclients is not None:
retval = (len(node.clients) <= maxclients)
else:
retval = True
return node.owner \
and node.owner.op == op \
and (len(node.clients) <= maxclients if maxclients is not None else True)
and retval
#backport
# and (len(node.clients) <= maxclients if maxclients is not None else True)
class GemmLocalOptimizer(LocalOptimizer):
"""This is a massive beast for recognizing all the ways that a subtraction or addition
......
theano/tensor/elemwise.py
浏览文件 @ 3126f874
......@@ -2,13 +2,13 @@ import sys
import elemwise_cgen as cgen
import numpy
from .. import gof
from ..gof import Op, Apply
from .. import scalar
from ..scalar import Scalar
from .. import printing
from ..printing import pprint
from ..gof.python25 import all
from theano import gof
from theano.gof import Op, Apply
from theano import scalar
from theano.scalar import Scalar
from theano import printing
from theano.printing import pprint
from theano.gof.python25 import all
from copy import copy, deepcopy
......@@ -215,19 +215,31 @@ class DimShuffle(Op):
'0, 0, NPY_ALIGNED|NPY_ENSURECOPY, NULL)')]
shape_statements = ['npy_intp dimensions[%i]'%nd_out]
shape_statements += [('dimensions['+str(i)+'] = %(basename)s->dimensions['+str(o)+']')
if o != 'x' else
('dimensions['+str(i)+'] = 1')
for i, o in enumerate(self.new_order)]
for i, o in enumerate(self.new_order):
if o != 'x':
shape_statements += [('dimensions['+str(i)+'] = %(basename)s->dimensions['+str(o)+']')]
else:
shape_statements += [('dimensions['+str(i)+'] = 1')]
#backport
#shape_statements += [('dimensions['+str(i)+'] = %(basename)s->dimensions['+str(o)+']')
# if o != 'x' else
# ('dimensions['+str(i)+'] = 1')
# for i, o in enumerate(self.new_order)]
strides_statements = ['npy_intp strides[%i]'%nd_out]
#set the strides of the non-broadcasted dimensions
strides_statements += [('strides['+str(i)+'] = %(basename)s->strides['+str(o)+']')
if o != 'x' else
('strides['+str(i)+'] = 0')
for i, o in enumerate(self.new_order)]
for i, o in enumerate(self.new_order):
if o != 'x':
strides_statements += [('strides['+str(i)+'] = %(basename)s->strides['+str(o)+']')]
else:
strides_statements += [('strides['+str(i)+'] = 0')]
#backport
#strides_statements += [('strides['+str(i)+'] = %(basename)s->strides['+str(o)+']')
# if o != 'x' else
# ('strides['+str(i)+'] = 0')
# for i, o in enumerate(self.new_order)]
# set the strides of the broadcasted dimensions
# this algorithm is from numpy: PyArray_Newshape() in cvs/numpy/numpy/core/src/multiarraymodule.c
......@@ -442,7 +454,16 @@ class Elemwise(Op):
def _rehash(self):
items = self.inplace_pattern.items()
items.sort()
tuple_items = tuple([k for k,v in items] + [(tuple(v) if isinstance(v, (tuple, list)) else v) for k,v in items])
first_part = [k for k,v in items]
second_part = []
for k,v in items:
if isinstance(v, (tuple, list)):
second_part += [tuple(v)]
else:
second_part += [v]
tuple_items = tuple(first_part + second_part)
#backport
#tuple_items = tuple([k for k,v in items] + [(tuple(v) if isinstance(v, (tuple, list)) else v) for k,v in items])
h = hash('Elemwise') ^ hash(self.scalar_op) ^ hash(tuple_items)
assert h == getattr(self,'_hashval', h)
self._hashval = h
......@@ -517,10 +538,21 @@ class Elemwise(Op):
for dims in zip(*[[(1, True)]*(maxsize - len(input.shape)) + zip(input.shape, sinput.type.broadcastable)
for input, sinput in zip(inputs, node.inputs)]):
if max(d for d,b in dims) != 1 and (1, False) in dims:
msg = []
for input, sinput in zip(inputs, node.inputs):
for d, b in zip(input.shape, sinput.type.broadcastable):
if b:
msg += ['*']
else:
msg += [str(d)]
raise ValueError('Dimension mismatch; shapes are %s' %
', '.join('(%s)' % ', '.join('*' if b else str(d)
for d, b in zip(input.shape, sinput.type.broadcastable))
for input, sinput in zip(inputs, node.inputs)))
', '.join('(%s)' % ', '.join(msg)))
#backport
#raise ValueError('Dimension mismatch; shapes are %s' %
# ', '.join('(%s)' % ', '.join('*' if b else str(d)
# for d, b in zip(input.shape, sinput.type.broadcastable))
# for input, sinput in zip(inputs, node.inputs)))
# Other mismatches will be caught by the ufunc
if not self.inplace_pattern:
for output, storage in zip(node.outputs, output_storage):
......
theano/tensor/inplace.py
浏览文件 @ 3126f874
from .basic import _scal_elemwise #, _transpose_inplace
from .. import scalar as scal
from basic import _scal_elemwise #, _transpose_inplace
from theano import scalar as scal
import elemwise
from .. import printing
from ..printing import pprint
from theano import printing
from theano.printing import pprint
from theano.gof.python25 import any
def _scal_inplace(symbol):
"""Replace a symbol definition with an elementwise version of the corresponding scalar Op"""
......
theano/tensor/opt.py
浏览文件 @ 3126f874
......@@ -4,20 +4,20 @@
# TODO: 0*x -> 0
from .. import gof
from ..gof import opt, InconsistencyError, TopoOptimizer, graph
from theano import gof
from theano.gof import opt, InconsistencyError, TopoOptimizer, graph
from elemwise import Elemwise, DimShuffle
from .. import scalar
from theano import scalar
import basic as T
import inplace as I
import numpy as N
import operator
import itertools
import sys
from .. import compile #to register the optimizer built by this file
from ..compile.debugmode import _debugprint
from theano import compile #to register the optimizer built by this file
from theano.compile.debugmode import _debugprint
from theano.gof.python25 import any
# Utilities
......@@ -738,11 +738,20 @@ class Canonizer(gof.LocalOptimizer):
def mul_calculate(num, denum, aslist=False, out_type=None):
if not num and not denum:
# Smallest 1 possible.
return [] if aslist else N.int8(1)
if aslist:
return []
else:
return N.int8(1)
#return [] if aslist else N.int8(1)
# Make sure we do not accidently upcast data types.
if out_type is None:
# TODO: remove this error-causing heuristic
first = num[0] if num else denum[0]
if num:
first = num[0]
else:
first = denum[0]
#first = num[0] if num else denum[0]
one = N.asarray(first).dtype.type(1)
else:
one = N.asarray(1, dtype=out_type.dtype)
......@@ -850,15 +859,29 @@ def local_mul_specialize(node):
new_inputs.append(input)
if len(new_inputs) < len(node.inputs):
if len(new_inputs) == 0:
newval = -y.flatten()[0] if neg else y.flatten()[0]
if neg:
newval = -y.flatten()[0]
else:
newval = y.flatten()[0]
#newval = -y.flatten()[0] if neg else y.flatten()[0]
return fill_chain(T.TensorConstant(T.TensorType(dtype=node.outputs[0].type.dtype,
broadcastable = [True] * node.outputs[0].ndim), N.asarray(newval)))
if len(new_inputs) == 1:
return fill_chain(-new_inputs[0] if neg else new_inputs[0])
if neg:
msg = -new_inputs[0]
else:
msg = new_inputs[0]
return fill_chain(msg)
# return fill_chain(-new_inputs[0] if neg else new_inputs[0])
else:
return fill_chain(-T.mul(*new_inputs) if neg else \
T.mul(*new_inputs))
if neg:
msg = -T.mul(*new_inputs)
else:
msg = T.mul(*new_inputs)
#return fill_chain(-T.mul(*new_inputs) if neg else \
# T.mul(*new_inputs))
else:
return False
register_specialize(local_mul_specialize)
......@@ -914,7 +937,11 @@ mul_canonizer = in2out(gof.LocalOptGroup(local_mul_canonizer, local_fill_cut, lo
def add_calculate(num, denum, aslist = False, out_type=None):
#TODO: make sure that this function and mul_calculate are similar
zero = 0.0 if out_type is None else N.asarray(0, dtype=out_type.dtype)
if out_type is None:
zero = 0.0
else:
zero = N.asarray(0, dtype=out_type.dtype)
#zero = 0.0 if out_type is None else N.asarray(0, dtype=out_type.dtype)
v = reduce(N.add, num, zero) - reduce(N.add, denum, zero)
if aslist:
if N.all(v == 0):
......@@ -1061,7 +1088,15 @@ def constant_folding(node):
storage = [[None] for output in node.outputs]
node.op.perform(node, [x.data for x in node.inputs], storage)
#TODO: think about how to extend to more types
return [(T.TensorConstant if isinstance(s[0], (N.ndarray,int,float)) else gof.Constant)(output.type, s[0]) for s, output in zip(storage, node.outputs)]
msg = []
for s, output in zip(storage, node.outputs):
if isinstance(s[0], (N.ndarray,int,float)):
msg += [T.TensorConstant(output.type,s[0])]
else:
msg += [gof.Constant(output.type, s[0])]
return msg
#TODO: verify this backport!!
#return [(T.TensorConstant if isinstance(s[0], (N.ndarray,int,float)) else gof.Constant)(output.type, s[0]) for s, output in zip(storage, node.outputs)]
register_canonicalize(constant_folding)
register_specialize(constant_folding)
......
theano/tensor/randomstreams.py
浏览文件 @ 3126f874
......@@ -4,9 +4,9 @@ __docformat__ = "restructuredtext en"
import sys
import numpy
from ..compile import module, In, Component
from ..gof import Container
from ..tensor import raw_random
from theano.compile import module, In, Component
from theano.gof import Container
from theano.tensor import raw_random
class RandomStreamsInstance(object):
"""RandomStreamsInstance"""
......@@ -37,7 +37,10 @@ class RandomStreamsInstance(object):
:rtype: None
"""
seed = self.default_seed if seed is None else seed
if seed is None:
seed = self.default_seed
#backport
#seed = self.default_seed if seed is None else seed
seedgen = numpy.random.RandomState(seed)
for old_r, new_r in self.random_streams.random_state_variables:
old_r_seed = seedgen.randint(2**30)
......
theano/tensor/raw_random.py
浏览文件 @ 3126f874
......@@ -7,8 +7,8 @@ import numpy
#local imports
import basic as tensor
import opt
from .. import gof
from ..compile import optdb
from theano import gof
from theano.compile import optdb
class RandomStateType(gof.Type):
"""A Type wrapper for numpy.RandomState
......@@ -85,7 +85,12 @@ class RandomFunction(gof.Op):
def __setstate__(self, state):
self.state = state
fn, outtype, args, kwargs = state
self.fn = getattr(numpy.random.RandomState, fn) if isinstance(fn, str) else fn
if isinstance(fn, str):
self.fn = getattr(numpy.random.RandomState, fn)
else:
self.fn = fn
#backport
#self.fn = getattr(numpy.random.RandomState, fn) if isinstance(fn, str) else fn
self.outtype = outtype
self.args = tuple(tensor.as_tensor_variable(arg) for arg in args)
self.inplace = kwargs.pop('inplace', False)
......@@ -139,7 +144,12 @@ class RandomFunction(gof.Op):
inputs = []
for arg, default in zip(args, self.args):
assert arg is None or default.type.dtype == arg.type.dtype
input = default if arg is None else arg
if arg is None:
input = default
else:
input = arg
#backport
#input = default if arg is None else arg
inputs.append(input)
return gof.Apply(self,
......
theano/tensor/tests/test_basic.py
浏览文件 @ 3126f874
......@@ -10,7 +10,7 @@ from copy import copy
from theano import compile
from theano import gradient
from theano import gof
from theano.gof.python25 import any
from theano.gof.python25 import any, all
from theano import gof
from theano.tensor.elemwise import DimShuffle
......
theano/tensor/tests/test_blas.py
浏览文件 @ 3126f874
import traceback
import theano.tensor as T
from ...gof import Env
from ...printing import pp
from theano.gof import Env
from theano.printing import pp
import numpy
from theano.tensor.blas import *
from theano.tensor.blas import _dot22, res_is_a
......@@ -13,7 +13,7 @@ _as_scalar = GemmLocalOptimizer._as_scalar
_is_real_matrix = GemmLocalOptimizer._is_real_matrix
from theano import In, Out
from .test_basic import (_approx_eq, as_tensor_variable, inplace_func,
from test_basic import (_approx_eq, as_tensor_variable, inplace_func,
compile, value, constant, inplace, eval_outputs)
class t_gemm(TestCase):
......@@ -415,4 +415,3 @@ def test_inplace1():
# gemm should operate in-place on (Z+Z)
if (not gemm in [n.op for n in f.maker.env.nodes]):
raise Failure('no gemm in graph')
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